A device for measuring dynamic vertical wheel loads was designed and implemented for the primary purpose of detecting abnormal vertical loads due to wheel irregularities. Using a special test train, loads generated by different types of irregularities were measured and documented. The device was installed on a revenue service rail line and is currently used to monitor traffic loads and detect wheel anomalies. A design overview and results of the field tests are presented and an analysis of revenue loads.
A device for automatically measuring, analyzing, and recording dynamic wheel/rail loads was designed and implemented as a result of an investigation of concrete tie track performance. The primary use of the device is the detection of the abnormal dynamic loads resulting from wheel tread irregularities, and the reporting of this information at a remote terminal. Using multiple microcomputers controlled by a 68000-based VME microcomputer system, the wheel impact load detector reads vertical wheel loads from strain gage patterns in the web of the rail in a series of successive tie cribs, sampling approximately seven to ten percent of each wheel circumference per crib. Different data options are available at a remote terminal, including all wheel loads (i.e., all axles, all measurement sites), loads exceeding either of two adjustable load thresholds, or cumulative load statistics (axle counts in speed and load bands).
The first wheel impact load detector was installed on a concrete tie section of Amtrak's high-speed Northeast Corridor rail line, and is currently being used both as a means for monitoring wheel conditions for wheel maintenance programs and as a tool for developing wheel load environment statistical descriptions. In this paper, a design overview and the results of experiments with a test train are presented. An analysis of revenue traffic dynamic wheel loads and their impact on track and equipment life is also discussed.
The authors have been involved with the measurement and characterization of wheel/rail loads through the use of wayside measurements over the last decade for the U.S. Department of Transportation (both the Federal Railroad Administration [FRA] and the Transportation Systems Center [TSC]), Amtrak, and the Association of American Railroads (AAR). The majority of these studies have included statistical characterizations of the loads generated by either revenue traffic [1] or special test consists [2]. In these and other test programs, the main area of interest focused on the loads generated by vehicle dynamics.
In June 1980, inspections of concrete crossties on the Northeast Corridor revealed numerous ties with transverse rail seat cracks. As part of a research program [3] being conducted at that time, it was determined that these cracks were being caused by high peak vertical loads generated by wheel tread irregularities on Amtrak passenger coaches. Investigations revealed that long wavelength, out-of-round conditions often existed on the worst wheels. These wheels were identified as causing the most severe vertical loads, sometimes exceeding 100 kips (445 kN). More significantly, these wheels were very difficult to detect through normal visual inspection, and in fact, often would pass existing geometry wheel condemning limits. As a result of these findings, Amtrak and DOT/FRA undertook a program to have Battelle's Columbus Laboratories develop, manufacture, install, and test a permanent monitoring device to detect wheels which produced excessive loads. The resulting wheel impact load detector was built and installed in mid-1983 on the Northeast Corridor near Edgewood, Md. Since that time, it has been used to accomplish various goals which are covered in this paper.
The initial problem which led to the development of the wheel impact load detector was early signs of tie rail seat cracking on portions of 400 track-miles (644 km) of concrete-tie track installed on Amtrak's Boston-to-Washington line. These "hairline"cracks were first detected during a program being conducted to correlate the performance of concrete tie track in revenue service with its performance at the Facility for Accelerated Service Testing [4]. Measurements in that program included vertical and lateral wheel/rail loads, tie center and rail seat bending moments, and rail and tie accelerations. The instrumentation methodology used to make these measurements and the data reductions performed are described in [5]. An example time history showing rail loads and tie strains is shown in FIG. 1. One of the field test measurement sites was located near Aberdeen, Md., where rail seat flexural cracks were discovered on this relatively new track as part of the site inspection and preparation for dynamic measurements. The first indication of impact loading occurred from examination of tie bending moment oscillographic traces, which showed that tie response under wheels with surface irregularities was highly oscillatory, typically in "tone bursts", which are evident in FIG. 1. However, rail seat bending mements up to only 220 kip-in (25 kN-m) and vertical wheel/rail loads up to 65 kips (290 kN) were observed, which is well below the 375 kip-in (42 kN-m) cracking thresholds identified in laboratory tests. These data, however, used a 300-Hz, low-pass filter for analysis. This bandwidth was determined from previous analysis to be more than adequate when measuring loads due to normal wheel passage. In a further review of the Aberdeen measurements, the data were processed with low-pass filters set at 2 kHz, and one peak rail seat bending moment of 370 kip-in (42 kN-m) was measured in the 8-day block of data [6]. This clearly showed that tie rail seat craking could be caused by these relatively frequent impact loads.
The full effects of dynamic loading are illustrated in FIG. 2, which compares the cumulative distribution of both the calculated static and the measured dynamic wheel loads. The static loads were determined by acquiring revenue consist lists throughout the period of dynamic data collection, and tabulating the gross loads of the cars listed to develop the cumulative curve. This allowed for direct statistical comparisons between static and dynamic loads without direct knowledge of the static weights of the individual axles.
The variation between the static and dynamic load curves at any one point can be caused by four factors: (1) Static weight distribution to each wheel on any car will rarely be exactly 1/8 of the gross load listed on the train consist sheet. Uneven car loading, as well as imperfect load distribution within a truck's suspension, will cause a variability in the loads seen at each wheel; (2) Dynamic wheel impacts caused by irregularities in either the wheels or the rail surfaces; (3) Variation of wheel force due to vehicle/track interaction, such as curving imbalance, car rocking, and pitch and bounce; (4) Differences in calibration between the scales used to measure the gross carloads and the circuits used to measure the dynamic wheel loads.
FIG. 2 shows a relatively close matching of the loads determined statically and dynamically over 90 to 95 percent of the axles. On the static curves, the near-vertical line segments represent subpopulations of vehicles which are listed in the consists as having identical gross loads. The corresponding segments of the dynamic curves typically have finite slopes which indicate the normal scatter in actual wheel loads about the average of these subpopulations. In the lower portion of the plot, static and dynamic loads begin to diverge significantly because of the superposition on the dynamic load curve of an additional subpopulation of loads from wheels having tread irregularities, including spalled and eccentric profiles and slid flats. Although a direct interpretation of the two curves in this low-probability, high-load region might imply that these higher loads caused by wheel irregularities are being superimposed only on the heaviest nominal wheels, a detailed examination of the wheel load data shows that nominally lighter wheels also contribute to these incremental dynamic loads. It has been shown [7] that the dynamic increment is governed almost entirely be unsprung mass such that car load is additive rather than multiplicative.
It should also be emphasized that these data were collected on well-maintained track without rail surface irregularities or visible geometry errors, and that a more comprehensive indentification of impact loading and the wheels which cause it was needed.
The measurement of vertical wheel loads in the aforementioned programs was accomplished using a circuit adapted from strain gage patterns reported by the ORE [8, 9]. This pattern, shown in FIGS. 3 and 4, measures the net shear force differential between the two gaged regions, a-b and c-d as in the diagram. With the gage pattern placed within a free span of rail (the "crib" space between crossties), the circuit output is directly proportional to the vertical load, V, as it passes between the gages. The influence zone of the pattern is short for a normal crib width, typically 4 to 6 inches (10 to 15 cm) less than the distance between a-b and C-d, so that only a sample of short time duration is provided from each passing wheel. From laboratory and field tests, this pattern has shown excellent linearity and minimal sensitivity to lateral load (cross talk) or to the lateral position of the vertical load.
The output signal for a single wheel passing three typical gage circuit installations is shown in FIG. 1. A smooth wheel rolling over a circuit installed in a wide crib will produce a trapezoidal-shaped signal with uniform sensitivity over the center portion of the signal. As the speed of the passing wheel increases, two effects have influence on the output signal. The first is the frequency response of the measurement, including effective rail mass and dynamic stiffness effects, and signal conditioning. The second effect is the load variation introduced by wheel or rail irregularitites and vehicle dynamics. Rail mass effects are negligibly small compared to the wheelset mass which induces the dynamic load. The rail mass is roughly that associated with the span between the gages. Some rounding of the waveshape into a smoothed trapezoidal pulse is noticeable at speed, and is due to the combined dynamic effect. Although this effect does not change the peak value obtained from the center of the circuit, it does tend to attenuate the "shoulders" of the circuit's response slightly. A similar effect can be caused by using signal conditioning with too low a frequency cut-off. As discussed earlier, this will significantly reduce the peak response of the circuit, causing underestimation of impact load whenever signal bandwidth is below about 2 kHz [6].
FIG. 1 illustrates load time histories over several circuits. These signals are similar to those obtained from the circuit installations which are part of the Amtrak wheel impact load detector installation. The peak signal shown for site 1 is due to a wheel flat, and will be discussed in a later section. The load variations shown for sites 2 and 4 are due to minor wheel dynamics and/or imperfections.
The gage circuits which were installed on the first Northeast Corridor system are arranged so that the trapezoidal "influence zone" has a full amplitude portion of roughly 8 inches (20 cm) in length.
In FIG. 1, the circuit output from site 1 showed a wheel impact superimposed on the nominal wheel load. This pulse was approximately a half-sine wave of 3 milliseconds duration, representing an impact load of 55 kips (250 kN). Field experience has shown that an impact pulse varies in both duration and magnitude with train speed and defect type. An impact pulse is typically one to three milliseconds in duration, but may be as short as one-half millisecond when caused by a small defect traveling at high speed. It is possible to obtain multiple impacts and zero values from a severe defect within the measurement "influence zone." It is also possible for wheels to "leap over" a measurement site if a severe defect is encountered just before the measurement site, causing the wheel to "lift off" and impact the rail beyond the actual measurement zone. Another phenomenon associated with severe impacts is rail ringing, which occurs when a severe rail impacts sets up shear and bending waves in the rail. These are usually exhibited as a resonant stress wave well within the necessary 2 kHz bandwidth which travels down the rail and produces signals simultaneously, within the time frame of interest, at adjacent instrumented locations. This traveling wave can produce rail circuit outputs which are greater than those induced by empty freight cars.
After the signal produced by the load measuring circuit was properly characterized using field instrumentation, it became possible to define the requirements for a system to detect wheel impacts in an automated, single purpose device. The major design requirements for data acquistion will be discussed first, followed by data reduction requirements. Finally, system integration contraints will be addressed.
The major goal of the original wheel impact load detector system was to detect and identify wheel tread imperfections which cause damage to concrete tie track. These imperfections may occur anywhere along the circumference of a wheel, which for a standard 36 inch (91 cm) wheel, translates into approximately 110 inches (2.8 m) of tread to be inspected. Since the current measurement circuit used has discrete "influence zones" of about 8 inches (20 cm) in length, a number of circuits must be used to inspect a wheel on a single roll-by. For the wheel impact load detector constructed for Amtrak, four measurement circuits were used, giving about 30 percent inspection of each wheel as it passed the measurement array. Since Amtrak has a captive fleet, each wheel may pass the measurement array several times a week, and should therefore be subject to an inspection of the full wheel tread on no more than a semi-weekly basis. For other applications such as the inspection of interchange freight traffic, a larger measurement array would be desirable. By doubling the number of measurement circuits to eight and adjusting the circuit spacing, about 70 percent inspection of a 36 inch (91 cm) wheel is achieved.
It was decided to instrument a single rail for the measurement array since it was hypothesized that most wheel anomalies occur in pairs on an axle. Because this hypothesis has not been proven, it will be the subject of future research. For the initial system installations, any channel expansion which occured was along a single rail to accomplish a more complete inspection of a single wheel on an axle rather than partial inspection of both wheels.
Given the nature of the dynamic load signals, it was determined that for the true impact peak to be detected within 5 percent, the digital sample rate must be nearly 30 kHz for each rail circuit. At the other extreme, the system must be able to inspect a 600-axle freight moving at 25 mph (40 km/h), thus requiring continuous sampling for 6 to 8 minutes, which represents about 100 million data samples for an eight circuit system.